L. Battle, Remco Chang, Jeffrey Heer, M. Stonebraker
{"title":"Position statement: The case for a visualization performance benchmark","authors":"L. Battle, Remco Chang, Jeffrey Heer, M. Stonebraker","doi":"10.1109/DSIA.2017.8339089","DOIUrl":null,"url":null,"abstract":"Visualizations are an invaluable tool in the data analysis process, as they enable scientists to explore and interpret billions of datapoints quickly, and with just a few rendered images. However, many visualization systems are unable to keep up with the unprecedented accumulation of data through remote sensors, field sensors, medical and personal devices, social networks, and more. This is due to certain assumptions that many of these tools rely on, such as the assumption that these systems can store entire datasets directly in main memory. With so many datasets massive datasets available, ranging from the NASA MODIS satellite imagery dataset[3] to the Internet Movie Database [4] to Twitter streams [1], this assumption no longer matches reality.","PeriodicalId":308968,"journal":{"name":"2017 IEEE Workshop on Data Systems for Interactive Analysis (DSIA)","volume":"144 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Workshop on Data Systems for Interactive Analysis (DSIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DSIA.2017.8339089","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
Visualizations are an invaluable tool in the data analysis process, as they enable scientists to explore and interpret billions of datapoints quickly, and with just a few rendered images. However, many visualization systems are unable to keep up with the unprecedented accumulation of data through remote sensors, field sensors, medical and personal devices, social networks, and more. This is due to certain assumptions that many of these tools rely on, such as the assumption that these systems can store entire datasets directly in main memory. With so many datasets massive datasets available, ranging from the NASA MODIS satellite imagery dataset[3] to the Internet Movie Database [4] to Twitter streams [1], this assumption no longer matches reality.